Cited by 139Gut microbiota and healthAir Quality and Health ImpactsOral microbiology and periodontitis research

Exposure to traffic-related air pollution and the composition of the gut microbiota in overweight and obese adolescents

Open access
Alderete, Tanya L., Jones, Roshonda B., Chen, Zhanghua, Kim, Jeniffer S., Habre, Rima, Lurmann, Frederick, Gilliland, Frank D., Goran, Michael I.·2018·Environmental Research

Abstract

Background Traffic-related air pollution (TRAP) exposure has been linked to type 2 diabetes and metabolic dysfunction in humans. Animal studies suggest that air pollutants may alter the composition of the gut microbiota, which may negatively impact metabolic health through changes in the composition and/or function of the gut microbiome.Objectives The primary aim of this study was to determine whether elevated TRAP exposure was correlated with gut bacterial taxa in overweight and obese adolescents from the Meta-AIR (Metabolic and Asthma Incidence Research) study. The secondary aim was to examine whether gut microbial taxa correlated with TRAP were also correlated with risk factors for type 2 diabetes (e.g., fasting glucose levels). We additionally explored whether correlations between TRAP and these metabolic risk factors could be explained by the relative abundance of these taxa.Methods Participants (17-19 years; n=43) were enrolled between 2014 and 2016 from Southern California. The CALINE4 line dispersion model was used to model prior year residential concentrations of nitrogen oxides (NOx) as a marker of traffic emissions. The relative abundance of fecal microbiota was characterized by 16S rRNA sequencing and spearman partial correlations were examined after adjusting for body fat percent.Results Freeway TRAP was correlated with decreased Bacteroidaceae (r=-0.48; p=0.001) and increased Coriobacteriaceae (r=0.48; p<0.001). These same taxa were correlated with fasting glucose levels, including Bacteroidaceae (r=-0.34; p=0.04) and Coriobacteriaceae (r=0.41; p<0.01). Further, freeway TRAP was positively correlated fasting glucose (r=0.45; p=0.004) and Bacteroidaceae and Coriobacteriaceae explained 24% and 29% of the correlation between TRAP and fasting glucose levels.Conclusions Increased TRAP exposure was correlated with gut microbial taxa and fasting glucose levels. Gut microbial taxa that were correlated with TRAP partially explained the correlation between TRAP and fasting glucose levels. These results suggest that exposure to air pollutants may negatively impact metabolic health via alterations in the gut microbiota.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.envres.2017.11.046

Cites

55 of 55 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Traffic-related air pollution can result in decreased relative abundance of Bacteroidaceae and increased relative abundance of Coriobacteriaceae.

    “Traffic-related air pollution can result in a decreased relative abundance of Bacteroidaceae and an increased relative abundance of Coriobacteriaceae (Alderete et al., 2018).”

    From Gut reactions: Breaking down xenobiotic–microbiome interactions (2019) · cites this paper as Alderete et al., 2018

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Alderete, T. L., Jones, R. B., Chen, Z., Kim, J. S., Habre, R., Lurmann, F., Gilliland, F. D., & Goran, M. I.
Affiliations
  • University of Southern California (US)
  • Sonoma Technology (United States) (US)
Corresponding author
Alderete, Tanya L.
Venue
Environmental Research
Publisher
Elsevier BV
Published
2018-02
Volume
161
Pages
472-478
ISSN
0013-9351 (ISSN-L)
OpenAlex
W2780157784
Cited by
139
References
55
Citations by year
2026: 9 · 2025: 18 · 2024: 25 · 2023: 23 · 2022: 21 · 2021: 7 · 2020: 21 · 2019: 10 · 2018: 4
FWCI
3.91
Type
journal article
Language
en
Open access
Locations
  • Environmental Research (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Funders
NIH NIEHS (K99ES027853, P30ES007048, P01ES022845)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Air Quality and Health Impacts
  • Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
Keywords
traffic-related air pollution, gut microbiota, adolescents, overweight, obesity, type 2 diabetes risk, fasting blood glucose, nitrogen oxides, Bacteroidaceae, Coriobacteriaceae, metabolic health, fecal microbiota
MeSH terms
Gastrointestinal Microbiome, Adolescent, Air Pollution, Vehicle Emissions, California, Diabetes Mellitus, Type 2, Female, Humans, Male, Obesity, Risk, RNA, Ribosomal, 16S, Overweight

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review